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Record W2410217283 · doi:10.2310/7750.2013.13102

Skin Conditions in Community-Living Older Adults

2014· article· en· W2410217283 on OpenAlexafffundabout
Samantha Gontijo Guerra, Helen‐Maria Vasiliadis, Michel Préville, Djamal Berbiche

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicDermatological diseases and infestations
Canadian institutionsHôpital Charles-Le MoyneUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsMedicineEpidemiologyGerontologyPopulationHealth careGeriatricsEnvironmental healthPathologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: There are considerable gaps in the knowledge of the global epidemiology of skin conditions in the geriatric population. OBJECTIVE: This study attempted to (1) determine the frequency of skin conditions, (2) evaluate the agreement between two different data sources of information (self-report versus administrative), and (3) document medical care service use for skin conditions in a representative sample of community-dwelling older adults. METHODS: A secondary analysis using data from a longitudinal population-based health survey conducted in Quebec (2005-2008) within a sample of 2,811 community-dwelling older adults. RESULTS: Our results highlighted a high prevalence rate of self-reported (13%) and diagnosed skin conditions (21%). Agreement between data sources was low (kappa < 0.20). Most dermatologic-related medical visits were made to dermatologists (almost 60%). CONCLUSION: The epidemiology of skin conditions in the geriatric population is an under researched field, despite its important prevalence and relevance as a source of information for assessing the health care needs of older adults.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.288
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2014
Admission routes3
Has abstractyes

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